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Material Science and Machine Learning II

ORAL · Y32 · ID: 48678

Presentations

  • Data-driven estimation of transfer integrals in undoped cuprates

    ORAL

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    Presenters

    • Denys Y Kononenko

      Institute for Theoretical Solid State Physics, Leibniz IFW Dresden, Dresden, Germany

    Authors

    • Denys Y Kononenko

      Institute for Theoretical Solid State Physics, Leibniz IFW Dresden, Dresden, Germany

    • Ulrich K Rößler

      Institute for Theoretical Solid State Physics, Leibniz IFW Dresden, Dresden, Germany

    • Jeroen van den Brink

      Institute for Theoretical Solid State Physics, Leibniz IFW Dresden, Dresden, Germany, Institute for Theoretical Physics, TU Dresden, Dresden, Germany, IFW - Dresden

    • Oleg Janson

      Institute for Theoretical Solid State Physics, Leibniz IFW Dresden, Dresden, Germany, IFW Dresden

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  • High-Throughput Screening of Semiconductors for Artificial Photosynthesis with Data-Mining and First Principles Calculations

    ORAL

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    Publication: "High-Throughput Screening of Semiconductors of earth-abundant elements for Artificial Photosynthesis with Data-Mining and First Principles Calculations", Stafford, Aduenko, Mendoza-Cortes, in prep., 2021

    Presenters

    • Sean M Stafford

      Florida State University

    Authors

    • Sean M Stafford

      Florida State University

    • Jose L Mendoza-Cortes

      Michigan State University

    • Alexander Aduenko

      Moscow Institute of Physics and Technology

    • Jose L Mendoza-Cortes

      Michigan State University

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  • Accelerated materials discovery of complex multicomponent alloys and ceramics with deep reinforcement learning

    ORAL

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    Publication: Pimachev, A. K., & Neogi, S. (2021). First-principles prediction of electronic transport in fabricated semiconductor heterostructures via physics-aware machine learning. npj Computational Materials, 7(1), 1-12.

    Presenters

    • Artem Pimachev

      University of Colorado, Boulder

    Authors

    • Artem Pimachev

      University of Colorado, Boulder

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  • A neural network potential for high throughput screening of the energetics and thermodynamical stabilities of non-stoichiometric Chromium Sulfides

    ORAL

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    Presenters

    • Akram Ibrahim

      University of Maryland Baltimore County, University of Maryland, Baltimore County

    Authors

    • Akram Ibrahim

      University of Maryland Baltimore County, University of Maryland, Baltimore County

    • Daniel Wines

      University of Maryland, Baltimore County

    • Can Ataca

      University of Maryland, Baltimore County

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  • Crystal Diffusion Variational Autoencoder for Periodic Material Generation

    ORAL

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    Publication: Arxiv: https://arxiv.org/abs/2110.06197<br>Under review at the Tenth International Conference on Learning Representations (ICLR 2022)

    Presenters

    • Tian Xie

      Massachusetts Institute of Technology

    Authors

    • Tian Xie

      Massachusetts Institute of Technology

    • Xiang Fu

      Massachusetts Institute of Technology MI, Massachusetts Institute of Technology

    • Octavian Ganea

      Massachusetts Institute of Technology

    • Regina Barzilay

      Massachusetts Institute of Technology

    • Tommi S Jaakkola

      Massachusetts Institute of Technology

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  • Predicting elastic properties of crystal structures using rotationally equivariant graph neural networks

    ORAL

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    Presenters

    • Teerachote Pakornchote

      Chula Intelligent and Complex Systems Lab, and Extreme Conditions Physics Research Laboratory and Energy Materials Research Unit, Chulalongkorn University, Thailand

    Authors

    • Teerachote Pakornchote

      Chula Intelligent and Complex Systems Lab, and Extreme Conditions Physics Research Laboratory and Energy Materials Research Unit, Chulalongkorn University, Thailand

    • Annop Ektarawong

      Chula Intelligent and Complex Systems Lab, and Extreme Conditions Physics Research Laboratory and Energy Materials Research Unit, Chulalongkorn University, Thailand

    • Thiparat Chotibut

      Chula Intelligent and Complex Systems Lab, Department of Physics, Chulalongkorn University, Thailand, Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand, Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Thailand

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  • Machine learning to establish zero point energy as a screening parameter for identifying vibrationally stable perovskites

    ORAL

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    Publication: Manuscript submitted to Advanced materials, Wiley

    Presenters

    • Krishnaraj Kundavu

      Indian Institute of Technology, Bombay, Indian Institute of Technology Bombay, IIT Bombay

    Authors

    • Krishnaraj Kundavu

      Indian Institute of Technology, Bombay, Indian Institute of Technology Bombay, IIT Bombay

    • Amrita Bhattacharya

      Indian Inst of Tech-Bombay

    • Suman Mondal

      Indian Institute of Technology, Bombay, Indian Institute of Technology Bombay

    • Souvik Hui

      Indian Institute of Technology, Bombay

    • Rushikesh Rathod

      Indian Institute of Technology, Bombay

    View abstract →